{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2d1d6ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2022-2023-02\n",
    "\n",
    "Python Data Analysis Course(PDAC)\n",
    "\n",
    "主讲：周圳\n",
    "\n",
    "资源：耿远昊\n",
    "\n",
    "week01:数据科学-准备\n",
    "\n",
    "jupyter notebook 扩展"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ea77b4d",
   "metadata": {},
   "source": [
    "# jupyter notebook键盘快捷键"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09e92a6f",
   "metadata": {},
   "source": [
    "# 进入命令模式之后（此时你没有活跃单元），你可以尝试以下快捷键：\n",
    "* A 会在活跃单元之上插入一个新的单元，B 会在活跃单元之下插入一个新单元。\n",
    "* 连续按两次 D，可以删除一个单元。\n",
    "* 撤销被删除的单元，按 Z。\n",
    "* Y 会将当前活跃的单元变成一个代码单元。\n",
    "* 按住 Shift +上或下箭头可选择多个单元。在多选模式时，按住 Shift + M 可合并你的选择。\n",
    "* 按 F 会弹出「查找和替换」菜单。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cae02e63",
   "metadata": {},
   "source": [
    "# 处于编辑模式时（在命令模式时按 Enter 会进入编辑模式），你会发现下列快捷键很有用：\n",
    "* Ctrl + Home 到达单元起始位置。\n",
    "* Ctrl + S 保存进度。\n",
    "* 如之前提到的，Ctrl + Enter 会运行你的整个单元块。\n",
    "* Alt + Enter 不止会运行你的单元块，还会在下面添加一个新单元。\n",
    "* Ctrl + Shift + F 打开命令面板。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85106041",
   "metadata": {},
   "source": [
    "# 课程资源介绍\n",
    "## [joyfulpandas]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f37c88f1",
   "metadata": {},
   "source": [
    "# Python 基础回顾（预备知识）\n",
    "列表推导式与条件赋值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "18e757b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "student_index = [1000001,1000002,1000003,1000004,1000005,1000006]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "296a1d04",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 需求： 学号 奇数先筛选出来"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "00e11ece",
   "metadata": {},
   "outputs": [],
   "source": [
    "奇数_students = []\n",
    "for i in student_index:\n",
    "    if i%2 != 0:\n",
    "        奇数_students.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "621f1307",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1000001, 1000003, 1000005]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "奇数_students"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d89112ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1000001, 1000003, 1000005]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 列表推导式---> [结果变量  for循环 循环体]  ==> 一切的循环都可以用推导式来写\n",
    "奇数_students = [i for i in student_index if i%2 !=0] \n",
    "奇数_students "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b2bcd1fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a_c', 'a_d', 'b_c', 'b_d']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 课本的例子\n",
    "results = [m+'_'+n for m in ['a','b'] for n in ['c','d']] \n",
    "results "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "23a37a9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = []\n",
    "for m in ['a','b']:\n",
    "    for n in ['c','d']:\n",
    "        results.append(m+'_'+n) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "de7a1f73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a_c', 'a_d', 'b_c', 'b_d']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results "
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "f47965e4",
   "metadata": {},
   "source": [
    "# 匿名函数与 map 方法\n",
    "# zip 对象与 enumerate 方法\n",
    "# Numpy基础（略，有兴趣的同学可自学加强）\n",
    "# 文件的读取和写入（P27）\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "98309a03",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6ced925d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>排名</td>\n",
       "      <td>排名变化</td>\n",
       "      <td>企业</td>\n",
       "      <td>价值（亿元人民币）</td>\n",
       "      <td>价值变化（亿元人民币）</td>\n",
       "      <td>总部</td>\n",
       "      <td>行业</td>\n",
       "      <td>成立年份</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>抖音</td>\n",
       "      <td>13400</td>\n",
       "      <td>-10050</td>\n",
       "      <td>北京</td>\n",
       "      <td>社交媒体</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>8400</td>\n",
       "      <td>1680</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>航天</td>\n",
       "      <td>2002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-1</td>\n",
       "      <td>蚂蚁集团</td>\n",
       "      <td>8000</td>\n",
       "      <td>-2010</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>Stripe</td>\n",
       "      <td>4100</td>\n",
       "      <td>-2230</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>Shein</td>\n",
       "      <td>4000</td>\n",
       "      <td>2680</td>\n",
       "      <td>广州</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>币安</td>\n",
       "      <td>3000</td>\n",
       "      <td>2010</td>\n",
       "      <td>马耳他</td>\n",
       "      <td>区块链</td>\n",
       "      <td>2017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>Databricks</td>\n",
       "      <td>2500</td>\n",
       "      <td>0</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>大数据</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>2200</td>\n",
       "      <td>200</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>京东科技</td>\n",
       "      <td>2000</td>\n",
       "      <td>0</td>\n",
       "      <td>北京</td>\n",
       "      <td>数字科技</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>Checkout.com</td>\n",
       "      <td>1900</td>\n",
       "      <td>870</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0     1             2          3            4    5     6     7\n",
       "0   排名  排名变化            企业  价值（亿元人民币）  价值变化（亿元人民币）   总部    行业  成立年份\n",
       "1    1     0            抖音      13400       -10050   北京  社交媒体  2012\n",
       "2    2     1        SpaceX       8400         1680  洛杉矶    航天  2002\n",
       "3    3    -1          蚂蚁集团       8000        -2010   杭州  金融科技  2014\n",
       "4    4     0        Stripe       4100        -2230  旧金山  金融科技  2010\n",
       "5    5    11         Shein       4000         2680   广州  电子商务  2012\n",
       "6    6    15            币安       3000         2010  马耳他   区块链  2017\n",
       "7    7     1    Databricks       2500            0  旧金山   大数据  2013\n",
       "8    8     3          微众银行       2200          200   深圳  金融科技  2014\n",
       "9    9     2          京东科技       2000            0   北京  数字科技  2013\n",
       "10  10    11  Checkout.com       1900          870   伦敦  金融科技  2012"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_html('https://hurun.net/zh-CN/Info/Detail?num=L9SQPH9FKJB1')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "aa80851f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.read_html('https://hurun.net/zh-CN/Info/Detail?num=L9SQPH9FKJB1')[0].to_excel('output_hurun.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d8bc5256",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4, 6, 8]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(lambda x: 2*x,range(5)))"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    },
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "d8c33639",
   "metadata": {},
   "source": [
    "# 基本的数据结构（P31）\n",
    "![image.png](attachment:image.png)\n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "62d5d75d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cb78df07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>排名</td>\n",
       "      <td>排名变化</td>\n",
       "      <td>企业</td>\n",
       "      <td>价值（亿元人民币）</td>\n",
       "      <td>价值变化（亿元人民币）</td>\n",
       "      <td>总部</td>\n",
       "      <td>行业</td>\n",
       "      <td>成立年份</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>22500</td>\n",
       "      <td>17300</td>\n",
       "      <td>北京</td>\n",
       "      <td>社交媒体</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>-1</td>\n",
       "      <td>蚂蚁集团</td>\n",
       "      <td>10000</td>\n",
       "      <td>0</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>6400</td>\n",
       "      <td>4000</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>航天</td>\n",
       "      <td>2002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Stripe</td>\n",
       "      <td>6000</td>\n",
       "      <td>3800</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>53</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>3000</td>\n",
       "      <td>2600</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>102</td>\n",
       "      <td>Canva</td>\n",
       "      <td>2600</td>\n",
       "      <td>2400</td>\n",
       "      <td>悉尼</td>\n",
       "      <td>软件服务</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>24</td>\n",
       "      <td>Instacart</td>\n",
       "      <td>2500</td>\n",
       "      <td>1900</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>快递</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>40</td>\n",
       "      <td>Databricks</td>\n",
       "      <td>2400</td>\n",
       "      <td>2000</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>大数据</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>菜鸟网络</td>\n",
       "      <td>2200</td>\n",
       "      <td>450</td>\n",
       "      <td>杭州</td>\n",
       "      <td>物流</td>\n",
       "      <td>2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>38</td>\n",
       "      <td>Revolut</td>\n",
       "      <td>2100</td>\n",
       "      <td>1700</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0     1           2          3            4      5     6     7\n",
       "0   排名  排名变化          企业  价值（亿元人民币）  价值变化（亿元人民币）     总部    行业  成立年份\n",
       "1    1     1        字节跳动      22500        17300     北京  社交媒体  2012\n",
       "2    2    -1        蚂蚁集团      10000            0     杭州  金融科技  2014\n",
       "3    3     2      SpaceX       6400         4000    洛杉矶    航天  2002\n",
       "4    4     1      Stripe       6000         3800    旧金山  金融科技  2010\n",
       "5    5    53      Klarna       3000         2600  斯德哥尔摩  金融科技  2005\n",
       "6    6   102       Canva       2600         2400     悉尼  软件服务  2012\n",
       "7    7    24   Instacart       2500         1900    旧金山    快递  2012\n",
       "8    8    40  Databricks       2400         2000    旧金山   大数据  2013\n",
       "9    9     0        菜鸟网络       2200          450     杭州    物流  2013\n",
       "10  10    38     Revolut       2100         1700     伦敦  金融科技  2015"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_html('https://www.hurun.net/zh-CN/Info/Detail?num=Q9M3TQXA81M9')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e396045a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
